FAM117B Antibody

What is FAM117B and why are antibodies against it important for research?

FAM117B is a 589-amino acid protein encoded by a highly conserved gene across animal cells. It has been implicated in multiple pathological conditions including gastric cancer progression, lacunar stroke, and sarcoidosis . Antibodies against FAM117B are crucial research tools for investigating its expression patterns, protein-protein interactions, and subcellular localization. Studies have shown that FAM117B competes with NRF2 for KEAP1 binding through its ETGE motif, leading to reduced ubiquitination and degradation of NRF2, subsequently activating the KEAP1/NRF2 signaling pathway . This mechanism has significant implications for cancer cell growth and drug resistance. High-quality antibodies enable precise detection of FAM117B in various experimental contexts, from basic protein expression studies to complex mechanistic investigations of its role in disease progression.

What methods can be used to validate the specificity of a FAM117B antibody?

Validating FAM117B antibody specificity requires multiple complementary approaches:

• Knockout/knockdown validation: Compare antibody signals between wild-type samples and those with FAM117B knockdown (using shRNA, as demonstrated in gastric cancer cell lines) or knockout models . A specific antibody will show significantly reduced signal in FAM117B-depleted samples.

• Overexpression validation: Test the antibody on samples with deliberate FAM117B overexpression, which should show increased signal intensity compared to control samples.

• Western blot analysis: Confirm that the antibody detects a single band at the expected molecular weight (~65 kDa for FAM117B). Multiple bands may indicate cross-reactivity with other proteins.

• Immunoprecipitation followed by mass spectrometry: This can verify that the antibody specifically pulls down FAM117B protein rather than other related family members or proteins with similar epitopes.

• Peptide competition assay: Pre-incubation of the antibody with the immunizing peptide should abolish signal in immunoassays if the antibody is specific.

When working with FAM117B antibodies, validation is particularly important as the protein contains an ETGE motif that is also present in other proteins that interact with KEAP1 .

What are appropriate positive and negative controls for FAM117B antibody experiments?

Appropriate controls for FAM117B antibody experiments include:

Positive controls:

• Cell lines with confirmed high FAM117B expression, such as HGC-27, AGS, and SNU-668 gastric cancer cell lines

• Tissue samples from gastric cancer patients, which have been shown to have elevated FAM117B expression

• Cells or tissues with engineered FAM117B overexpression using expression plasmids

• Recombinant FAM117B protein (for western blot or ELISA)

Negative controls:

• Cell lines with FAM117B knockdown using validated shRNA constructs (shFAM117B #1 and shFAM117B #2 have demonstrated strong knockdown efficiency)

• CRISPR/Cas9-mediated FAM117B knockout cells

• Tissues known to have minimal FAM117B expression

• Primary antibody omission controls

• Isotype-matched irrelevant antibodies to control for non-specific binding

For co-localization studies with KEAP1, both proteins should be detected in the cytoplasm as demonstrated by immunofluorescence assays in gastric cancer cell lines .

How can FAM117B expression be effectively detected in tissue samples?

Detection of FAM117B in tissue samples can be achieved through several methods:

• Immunohistochemistry (IHC): This technique has been successfully used to detect FAM117B protein levels in tumor tissues from gastric cancer patients . For optimal results:

  • Use antigen retrieval methods appropriate for formalin-fixed paraffin-embedded tissues

  • Titrate antibody concentration to minimize background while maintaining specific signal

  • Include positive and negative controls in each staining batch

  • Consider multiplexed IHC to simultaneously detect FAM117B and interacting partners like KEAP1 and NRF2

• Immunofluorescence: This method allows co-localization studies, as demonstrated in research showing cytoplasmic co-localization of FAM117B and KEAP1 . Use confocal microscopy for higher resolution subcellular localization.

• RNA in situ hybridization: This technique can be used to detect FAM117B mRNA expression when antibodies show cross-reactivity or when validating antibody specificity.

• Western blotting of tissue lysates: For semi-quantitative analysis of FAM117B protein levels across different tissue samples.

• Tissue microarrays: For high-throughput analysis of FAM117B expression across large cohorts of patient samples.

When interpreting results, consider that FAM117B and NRF2 co-overexpression has been associated with poor prognosis in gastric cancer patients .

What experimental approaches can be used to investigate FAM117B-protein interactions?

Several methodologically robust approaches can be used to study FAM117B-protein interactions:

• Co-immunoprecipitation (Co-IP): This technique has successfully demonstrated the interaction between endogenous FAM117B and KEAP1 proteins . Use antibodies against FAM117B to pull down protein complexes, then probe for interacting partners by western blot.

• GST pull-down assays: This approach can determine direct protein-protein interactions, as shown with FAM117B and KEAP1 . Express GST-tagged FAM117B (or fragments) and test binding with potential partners.

• Immunofluorescence co-localization: This has confirmed that FAM117B and KEAP1 co-localize in the cytoplasm of gastric cancer cell lines . Use confocal microscopy for high-resolution imaging.

• Proximity ligation assay (PLA): This technique can detect protein interactions with high sensitivity and specificity in situ, which would be valuable for investigating FAM117B interactions in tissue samples.

• Bimolecular fluorescence complementation (BiFC): This approach allows visualization of protein interactions in living cells.

• FRET/FLIM analysis: For detecting molecular proximity between FAM117B and its binding partners with nanometer resolution.

• Yeast two-hybrid screening: This can identify novel FAM117B-interacting proteins.

For studying the specific interaction between FAM117B and KEAP1, focus on the ETGE motif in FAM117B, which has been shown to be critical for this interaction .

How can I design experiments to investigate the role of FAM117B in chemoresistance mechanisms?

Designing experiments to investigate FAM117B's role in chemoresistance requires a multi-faceted approach:

• Cell viability and apoptosis assays: Compare chemotherapeutic drug sensitivity in:

  • FAM117B knockdown cells (using validated shRNAs)

  • FAM117B-overexpressing cells

  • FAM117B ETGE motif mutant cells

  • Control cells

  Research has shown that FAM117B knockdown significantly weakened chemoresistance, while FAM117B overexpression enhanced it .

• Mechanistic studies focusing on the KEAP1/NRF2 pathway:

  • Simultaneously manipulate FAM117B and NRF2 expression (e.g., FAM117B overexpression in NRF2-silenced cells)

  • Measure NRF2 target gene expression (e.g., antioxidant response elements)

  • Assess ROS levels using flow cytometry with H2DCFDA or similar probes

  • Examine NRF2 subcellular localization (cytoplasmic vs. nuclear) by cell fractionation followed by western blot

• Ubiquitination assays:

  • Analyze NRF2 ubiquitination levels in cells with modified FAM117B expression

  • Use proteasome inhibitors (e.g., MG132) to prevent degradation of ubiquitinated proteins

  • Perform co-immunoprecipitation to pull down NRF2 and probe for ubiquitin

• In vivo models:

  • Develop xenograft models with:

    • shControl + Vector

    • shControl + FAM117B

    • shNRF2 + Vector

    • shNRF2 + FAM117B

  • Treat with chemotherapeutic agents and monitor tumor growth, angiogenesis, and apoptosis

• Clinical correlation:

  • Analyze FAM117B and NRF2 expression in patient samples before and after chemotherapy

  • Correlate expression levels with treatment response and survival outcomes

These approaches will help establish whether FAM117B-induced chemoresistance is NRF2-dependent, as suggested by research showing that FAM117B lost its ability to promote drug resistance in NRF2-silenced cells .

What are the technical challenges in developing antibodies against the ETGE motif of FAM117B?

Developing antibodies specifically targeting the ETGE motif of FAM117B presents several technical challenges:

• Motif conservation and specificity issues:

  • The ETGE motif is conserved across multiple KEAP1-binding proteins including NRF2

  • Antibodies raised against this motif may cross-react with other ETGE-containing proteins

  • Extensive validation is required using cells expressing FAM117B with mutated ETGE motifs as negative controls

• Epitope accessibility:

  • The ETGE motif may be partially obscured in the native protein conformation

  • When FAM117B binds to KEAP1, the motif becomes engaged in protein-protein interactions, potentially limiting antibody access

  • Antibodies may preferentially detect free (unbound) FAM117B

• Conformation-dependent recognition:

  • The functionality of the ETGE motif depends on its specific conformation

  • Antibodies developed against linear peptides containing ETGE may fail to recognize the native conformation

  • Consider using conformationally constrained peptides as immunogens

• Validation strategies:

  • Use competition assays with synthetic ETGE-containing peptides

  • Compare reactivity in wild-type FAM117B versus ETGE-mutated variants

  • Perform epitope mapping to confirm precise binding sites

• Functional blocking potential:

  • Antibodies targeting the ETGE motif might interfere with the FAM117B-KEAP1 interaction

  • This creates opportunities for developing therapeutic antibodies but complicates use in detection assays

  • Control experiments should assess whether the antibody alters FAM117B function

Given that the ETGE motif is critical for FAM117B's competition with NRF2 for KEAP1 binding and subsequent effects on gastric cancer growth and chemoresistance , developing specific antibodies against this region would be valuable for both research and potential therapeutic applications.

How can post-translational modifications of FAM117B be detected using antibody-based techniques?

Detecting post-translational modifications (PTMs) of FAM117B requires specialized antibody-based approaches:

• Modification-specific antibodies:

  • Use antibodies specifically recognizing phosphorylated, ubiquitinated, SUMOylated, or acetylated forms of FAM117B

  • Validate antibody specificity using in vitro modified recombinant FAM117B

  • Compare signals before and after treatment with enzymes that remove specific modifications (e.g., phosphatases, deubiquitinases)

• Enrichment strategies followed by detection:

  • Immunoprecipitate FAM117B using general anti-FAM117B antibodies

  • Probe with modification-specific antibodies (anti-phospho, anti-ubiquitin, etc.)

  • Alternatively, enrich for modified proteins (e.g., using anti-ubiquitin antibodies) and then probe for FAM117B

• Mass spectrometry-complemented approaches:

  • Immunoprecipitate FAM117B under native or denaturing conditions

  • Analyze by mass spectrometry to identify and map PTMs

  • Use the findings to develop site-specific modification antibodies

• Proximity ligation assays (PLA):

  • Combine anti-FAM117B antibodies with antibodies against specific modifications

  • PLA signal will only occur when both antibodies are in close proximity

  • This approach allows in situ detection of modified FAM117B in fixed cells or tissues

• 2D gel electrophoresis:

  • Separate proteins by isoelectric point and molecular weight

  • Modified forms of FAM117B will appear as distinct spots

  • Identify spots by western blotting with anti-FAM117B antibodies

Although specific PTMs of FAM117B haven't been extensively characterized in the current literature, investigating these modifications could provide valuable insights into the regulation of FAM117B's ability to compete with NRF2 for KEAP1 binding .

What methodological approaches can distinguish between direct and indirect effects of FAM117B on the KEAP1/NRF2 pathway?

Distinguishing between direct and indirect effects of FAM117B on the KEAP1/NRF2 pathway requires rigorous methodological approaches:

• In vitro binding assays with purified components:

  • Use surface plasmon resonance (SPR) or isothermal titration calorimetry (ITC) to measure direct binding kinetics and affinity between purified FAM117B and KEAP1

  • Compare binding parameters with and without competing NRF2 protein

  • Perform with wild-type FAM117B and ETGE motif mutants to confirm specificity

• Domain mapping and mutational analysis:

  • Create FAM117B constructs with mutations in the ETGE motif and other regions

  • Assess each construct's ability to bind KEAP1 and affect NRF2 degradation

  • Research has shown that FAM117B-ETGE mutants lose the ability to promote growth and chemoresistance in gastric cancer cells

• Proximity-based assays in cells:

  • Use FRET or BRET to measure real-time interactions between fluorescently tagged FAM117B, KEAP1, and NRF2

  • Examine changes in interaction dynamics upon stimulation or inhibition of relevant pathways

  • These approaches can reveal the temporal relationship between FAM117B-KEAP1 binding and NRF2 stabilization

• Competitive binding assays:

  • Express constant amounts of KEAP1 and NRF2 with increasing concentrations of FAM117B

  • Measure KEAP1-NRF2 complex formation using co-immunoprecipitation

  • Direct competition would show dose-dependent displacement of NRF2 from KEAP1 by FAM117B

• Reconstitution experiments in KEAP1-null systems:

  • Use KEAP1 knockout cells to eliminate endogenous KEAP1-dependent effects

  • Re-introduce wild-type or mutant KEAP1 constructs

  • Test FAM117B's effects on NRF2 in these controlled systems

Evidence indicates that FAM117B directly competes with NRF2 for KEAP1 binding through its ETGE motif, reducing NRF2's ubiquitination and degradation, ultimately activating KEAP1/NRF2 signaling .

What considerations are important for developing therapeutic antibodies targeting FAM117B in cancer?

Developing therapeutic antibodies targeting FAM117B for cancer treatment involves several important considerations:

• Target validation and mechanism:

  • Confirm FAM117B's overexpression in patient samples and correlation with poor prognosis

  • Determine whether targeting the ETGE motif would be sufficient to disrupt FAM117B-KEAP1 interaction

  • Evaluate whether antibody-induced FAM117B neutralization can effectively restore chemosensitivity

  • Consider combinatorial approaches with chemotherapeutic agents, as FAM117B promotes chemoresistance

• Antibody format selection:

  • Evaluate different formats: conventional IgG, Fab fragments, single-chain antibodies, bispecific antibodies

  • Consider antibody-drug conjugates (ADCs) if FAM117B internalization occurs

  • Assess penetration into solid tumors, particularly for gastric cancers

• Epitope selection:

  • Target functionally critical domains like the ETGE motif

  • Consider accessibility of epitopes in the tumor microenvironment

  • Design antibodies that can access cytoplasmic FAM117B through various delivery strategies

• Preclinical testing framework:

  • Use cell line panels with varied FAM117B and NRF2 expression levels

  • Develop xenograft models similar to those used in mechanistic studies

  • Include patient-derived xenografts to better represent tumor heterogeneity

• Potential resistance mechanisms:

  • Investigate alternative pathways that might compensate for FAM117B inhibition

  • Assess whether direct NRF2 activation could bypass FAM117B dependence

  • Explore combination strategies to prevent resistance development

• Biomarker development:

  • Establish accurate methods to quantify FAM117B protein levels in patient samples

  • Develop assays to measure KEAP1/NRF2 pathway activity as pharmacodynamic markers

  • Identify patient populations most likely to benefit (e.g., those with FAM117B/NRF2 co-overexpression)

Given that FAM117B promotes gastric cancer growth and chemoresistance through the KEAP1/NRF2 pathway , therapeutic antibodies targeting this protein might restore chemosensitivity and improve treatment outcomes.

What cell models are most appropriate for studying FAM117B antibody specificity and functionality?

Selecting appropriate cell models for FAM117B antibody validation and functional studies requires careful consideration:

• Established gastric cancer cell lines:

  • HGC-27, AGS, and SNU-668 cells have been successfully used to study FAM117B function

  • These lines demonstrate detectable FAM117B expression and respond to FAM117B manipulation

  • They represent suitable models for antibody validation and functional studies

• Genetically modified cell systems:

  • FAM117B knockdown models: Cells stably expressing shFAM117B constructs (#1 and #2) that show strong knockdown efficiency

  • FAM117B overexpression models: Cells transfected with FAM117B expression plasmids

  • ETGE motif mutant models: Cells expressing FAM117B with mutated ETGE motifs to study domain-specific functions

  • NRF2-silenced models: Useful for studying FAM117B's NRF2-dependent effects

• Complementary manipulation models:

  • shControl + Vector

  • shControl + FAM117B

  • shNRF2 + Vector

  • shNRF2 + FAM117B

  • These combinations have been used successfully in xenograft models

• Cell models for antibody screening:

  • HEK293T cells: Useful for recombinant expression systems, as demonstrated with HA-tagged FAM117B and FLAG-tagged KEAP1

  • Paired isogenic cell lines: Wild-type versus FAM117B knockout cells

• Three-dimensional and co-culture models:

  • Spheroid cultures: To better mimic solid tumor architecture

  • Co-cultures with stromal cells: To account for microenvironment influences

  • Organoid models: To better represent tissue architecture and cellular heterogeneity

When evaluating antibody specificity, a combination of these models provides rigorous validation. For functional studies, the appropriate model depends on the specific aspect of FAM117B biology being investigated.

How should FAM117B antibodies be optimized for different applications (Western blot, IHC, IF, IP)?

Optimizing FAM117B antibodies for different applications requires specific technical approaches:

Western Blot Optimization:

• Sample preparation:

  • Use appropriate lysis buffers containing protease inhibitors to prevent degradation

  • Include phosphatase inhibitors if studying phosphorylated forms of FAM117B

  • Heat samples at appropriate temperatures (typically 95°C for 5 minutes) in reducing conditions

• Technical parameters:

  • Antibody dilution: Typically start with 1:1000 and adjust as needed

  • Blocking solution: 5% non-fat milk or BSA in TBST

  • Incubation times: Primary antibody overnight at 4°C; secondary antibody 1-2 hours at room temperature

  • Multiple washes with TBST between steps

Immunohistochemistry (IHC) Optimization:

• Sample preparation:

  • Optimize fixation conditions (duration, temperature)

  • Test different antigen retrieval methods (heat-induced epitope retrieval with citrate buffer pH 6.0 or EDTA buffer pH 9.0)

• Technical parameters:

  • Test antibody dilutions ranging from 1:50 to 1:500

  • Optimize incubation times and temperatures

  • Consider signal amplification systems for low-abundance targets

  • Use automated staining platforms for consistency in clinical applications

Immunofluorescence (IF) Optimization:

• Sample preparation:

  • Test different fixatives (4% paraformaldehyde, methanol, or acetone)

  • Optimize permeabilization conditions (0.1-0.5% Triton X-100, saponin, or digitonin)

• Technical parameters:

  • Antibody dilution typically ranging from 1:100 to 1:500

  • Block with 1-5% normal serum from the species of secondary antibody

  • Include DAPI for nuclear counterstaining

  • Use confocal microscopy for high-resolution imaging, particularly for co-localization studies with KEAP1

Immunoprecipitation (IP) Optimization:

• Sample preparation:

  • Use gentle lysis buffers to preserve protein-protein interactions

  • Pre-clear lysates with protein A/G beads to reduce non-specific binding

• Technical parameters:

  • Antibody amount: Typically 2-5 μg per 500 μg of total protein

  • Incubation time: Overnight at 4°C with gentle rotation

  • Washing stringency: Balance between removing non-specific binding and preserving specific interactions

  • Elution conditions optimized for downstream applications

For each application, include appropriate positive controls (gastric cancer cell lines with known FAM117B expression) and negative controls (FAM117B knockdown cells) .

What strategies can be used to overcome cross-reactivity issues with FAM117B antibodies?

Overcoming cross-reactivity issues with FAM117B antibodies requires systematic approaches:

• Epitope-focused antibody development:

  • Target unique regions of FAM117B that have minimal sequence homology with related proteins

  • Avoid highly conserved domains, particularly when generating antibodies against specific family members

  • Consider using peptides from unique regions rather than full-length protein as immunogens

• Antibody purification strategies:

  • Perform affinity purification using recombinant FAM117B protein

  • Implement negative selection against potential cross-reactive proteins

  • Use subtractive purification with lysates from FAM117B knockout cells

• Validation using genetic models:

  • Compare antibody signal between wild-type and FAM117B knockdown/knockout samples

  • Use cells with defined expression levels of potential cross-reactive proteins

  • Include siRNA/shRNA controls targeting FAM117B, similar to the validated shFAM117B constructs used in gastric cancer studies

• Technical optimization:

  • Adjust antibody concentration to minimize non-specific binding

  • Modify blocking conditions (concentration, composition, duration)

  • Increase washing stringency (buffer composition, number of washes, duration)

  • Optimize incubation times and temperatures

• Competition assays:

  • Pre-incubate the antibody with excess recombinant FAM117B protein

  • Compare results with and without competition to identify specific signal

• Advanced specificity testing:

  • Use mass spectrometry to identify all proteins immunoprecipitated by the antibody

  • Perform epitope mapping to precisely define the antibody's binding region

  • Test reactivity against a panel of related proteins

• Application-specific controls:

  • For IHC/IF: Include peptide competition controls

  • For Western blot: Verify that band size matches predicted molecular weight

  • For IP: Confirm pulled-down protein identity by mass spectrometry

Implementing these strategies will help ensure that observed signals truly represent FAM117B rather than cross-reactive proteins, a critical consideration when studying its role in complex pathways like KEAP1/NRF2 signaling .

How can I quantitatively assess FAM117B expression levels in correlation with clinical outcomes?

Quantitatively assessing FAM117B expression levels in correlation with clinical outcomes requires robust methodological approaches:

• Tissue microarray (TMA) analysis:

  • Construct TMAs containing cores from large patient cohorts

  • Perform standardized IHC staining for FAM117B

  • Use digital image analysis software to quantify staining intensity and percentage of positive cells

  • Calculate H-scores or other semi-quantitative metrics

  • Correlate with clinicopathological parameters and survival outcomes

• Multiplex immunofluorescence analysis:

  • Simultaneously detect FAM117B, NRF2, KEAP1, and other relevant markers

  • Use multispectral imaging systems for precise quantification

  • Analyze co-expression patterns and subcellular localization

  • Correlate co-expression of FAM117B and NRF2 with prognosis, as their co-overexpression represents an independent factor for poor prognosis in gastric cancer

• Quantitative protein analysis from clinical samples:

  • Extract proteins from fresh or frozen tissue samples

  • Perform quantitative western blotting with appropriate loading controls

  • Use ELISA or similar assays for higher-throughput quantification

  • Normalize FAM117B levels to total protein content

• Transcript-level analysis:

  • Perform RT-qPCR for FAM117B mRNA quantification

  • Use RNA-seq for broader transcriptomic profiling

  • Analyze correlation between mRNA and protein levels

  • Include NRF2 target genes to assess pathway activation

• Statistical analysis workflow:

  • Stratify patients based on FAM117B expression levels (high vs. low)

  • Perform Kaplan-Meier survival analysis

  • Use Cox proportional hazards models for multivariate analysis

  • Adjust for known prognostic factors

  • Calculate hazard ratios and confidence intervals

• Response prediction models:

  • Correlate FAM117B expression with response to chemotherapy

  • Develop predictive models incorporating FAM117B and NRF2 expression

  • Validate in independent patient cohorts

  • Consider combining with other biomarkers for improved predictive power

Research has shown that FAM117B and NRF2 protein levels are highly expressed in tumor tissues of gastric cancer patients, and their co-overexpression is associated with poor prognosis . These quantitative approaches will help establish FAM117B's clinical utility as a prognostic or predictive biomarker.

What is the optimal experimental design for investigating FAM117B's role in modulating the tumor microenvironment?

The optimal experimental design for investigating FAM117B's role in modulating the tumor microenvironment requires a comprehensive approach:

• In vivo xenograft models with manipulated FAM117B expression:

  • Establish xenografts with different FAM117B expression levels:

    • Control (vector only)

    • FAM117B overexpression

    • FAM117B knockdown (using validated shRNA constructs)

    • FAM117B with mutated ETGE motif

  • Compare tumor growth rates, angiogenesis, and immune cell infiltration

  • Research has shown that FAM117B promotes angiogenesis in an NRF2-dependent manner in gastric cancer xenografts

• Multiplex immunohistochemistry analysis of tumor microenvironment:

  • Stain for:

    • FAM117B and NRF2 expression

    • Vascular markers (CD31 for angiogenesis quantification)

    • Immune cell populations (T cells, macrophages, neutrophils)

    • Extracellular matrix components

  • Use digital pathology for quantitative spatial analysis

• 3D co-culture systems:

  • Develop spheroid co-cultures containing:

    • Cancer cells with modulated FAM117B expression

    • Endothelial cells

    • Immune cells

    • Fibroblasts

  • Analyze cellular interactions and organization

  • Measure angiogenic responses and immune cell behavior

• Secretome analysis:

  • Collect conditioned media from cells with different FAM117B expression levels

  • Perform proteomic analysis to identify secreted factors

  • Validate key factors by ELISA

  • Test functional effects of conditioned media on endothelial cells and immune cells

• RNA-seq and pathway analysis:

  • Compare transcriptomes of:

    • Tumor cells with different FAM117B expression

    • Stromal cells exposed to conditioned media from these tumor cells

  • Identify key pathways and secreted factors affected by FAM117B expression

  • Focus on NRF2-regulated genes involved in redox homeostasis and inflammation

• ROS analysis in the tumor microenvironment:

  • Measure ROS levels in tumors with different FAM117B expression

  • Analyze how FAM117B-mediated changes in ROS affect stromal cells

  • Research has shown that FAM117B overexpression downregulates ROS levels in an NRF2-dependent manner

• Therapeutic intervention studies:

  • Test how FAM117B targeting affects response to:

    • Immunotherapies

    • Anti-angiogenic agents

    • Conventional chemotherapies

This experimental design will provide comprehensive insights into how FAM117B influences the tumor microenvironment, building on findings that it promotes angiogenesis and inhibits apoptosis in an NRF2-dependent manner .

How should contradictory results between FAM117B antibody-based detection methods be reconciled?

Reconciling contradictory results between different FAM117B antibody-based detection methods requires a systematic troubleshooting approach:

• Methodological differences analysis:

  • Compare fixation and sample preparation protocols across methods

  • Evaluate epitope accessibility in different applications

  • Consider that certain fixatives may mask or alter epitopes

  • Assess whether denatured (Western blot) versus native (IP, IF) conditions affect antibody recognition

• Antibody-specific considerations:

  • Determine if different antibodies target distinct epitopes of FAM117B

  • Assess whether antibodies recognize different isoforms or post-translationally modified forms

  • Verify specificity of each antibody using FAM117B knockdown controls

  • Evaluate lot-to-lot variability that might explain discrepancies

• Biological factors:

  • Consider tissue/cell type-specific expression patterns

  • Evaluate subcellular localization differences (cytoplasmic localization has been confirmed for FAM117B)

  • Assess potential context-dependent protein interactions that might mask epitopes

  • Analyze whether KEAP1 binding affects antibody accessibility to FAM117B

• Validation through complementary approaches:

  • Confirm key findings using non-antibody methods:

    • mRNA detection (RT-qPCR, RNA-seq, in situ hybridization)

    • Mass spectrometry-based protein identification

    • Alternative protein tagging (e.g., GFP fusion proteins)

  • Compare results across multiple antibodies targeting different epitopes

• Technical validation experiment design:

  • Side-by-side testing of multiple antibodies on identical samples

  • Titration experiments to determine optimal antibody concentrations

  • Include appropriate positive and negative controls in each experiment

  • Verify antibody performance in cells with engineered FAM117B expression levels

• Systematic documentation and reporting:

  • Document exact protocols, antibody sources, catalog numbers, and lot numbers

  • Record all technical parameters (dilutions, incubation times, buffers)

  • Consider publishing detailed protocols to improve reproducibility

When faced with contradictory results, determine which method provides the most reliable data based on rigorous controls and reproducibility, particularly using the genetic manipulation approaches that have been validated in FAM117B research .

What are the potential pitfalls in interpreting FAM117B antibody staining patterns in tissue samples?

Interpreting FAM117B antibody staining patterns in tissue samples presents several potential pitfalls that researchers should address:

• Technical artifacts vs. biological signal:

  • Edge artifacts and uneven staining can be misinterpreted as biological gradients

  • Necrotic areas often show non-specific antibody binding

  • Fixation-induced autofluorescence may be mistaken for positive signal in fluorescence-based detection

  • Endogenous peroxidase activity can cause false-positive signals in IHC

• Heterogeneous expression patterns:

  • FAM117B expression may vary across different regions of the same tumor

  • Intratumoral heterogeneity requires systematic sampling approaches

  • Consider using whole slide imaging rather than relying on representative fields

  • Correlation of FAM117B with NRF2 expression should be assessed throughout the tumor, as their co-overexpression has prognostic significance

• Subcellular localization interpretation:

  • FAM117B has been shown to localize in the cytoplasm, where it interacts with KEAP1

  • Nuclear staining may represent cross-reactivity or unrecognized biology

  • Diffuse weak staining might indicate technical issues rather than low expression

  • Punctate patterns require careful validation to distinguish between specific staining and artifacts

• Specificity concerns:

  • Cross-reactivity with related proteins cannot be excluded without proper controls

  • Peptide competition controls should be included to confirm specificity

  • Adjacent normal tissue can serve as an internal control for specificity

  • FAM117B knockdown controls in cell line samples should be run in parallel

• Quantification challenges:

  • Visual scoring is subjective and prone to inter-observer variability

  • Digital image analysis requires standardized staining and image acquisition

  • Threshold setting for positive/negative classification affects results

  • H-scores or other semi-quantitative methods should be validated for reproducibility

• Contextual interpretation:

  • FAM117B expression should be interpreted in the context of KEAP1 and NRF2 expression

  • Consider the activation state of the KEAP1/NRF2 pathway

  • Correlate with clinical data and other molecular markers

  • Remember that FAM117B and NRF2 co-overexpression is an independent factor for poor prognosis

To minimize these pitfalls, use standardized protocols, include appropriate controls, employ multiple detection methods, and validate findings with functional assays.

How can I distinguish between FAM117B expression changes and technical variations in immunoassays?

Distinguishing between true FAM117B expression changes and technical variations in immunoassays requires rigorous experimental design and controls:

• Standardization of technical parameters:

  • Use consistent antibody lots, dilutions, and incubation conditions

  • Standardize sample preparation (fixation times, buffers, antigen retrieval methods)

  • Process all comparative samples simultaneously when possible

  • Use automated systems to minimize handling variations

• Inclusion of comprehensive controls:

  • Internal controls: Include samples with known FAM117B expression levels in each assay run

  • Loading controls: Use housekeeping proteins (e.g., GAPDH, β-actin) for Western blots

  • Tissue controls: Include normal adjacent tissue in IHC as internal reference

  • Genetic controls: When available, include FAM117B knockdown samples as negative controls

  • Serial dilution controls: Perform antibody titrations to ensure operation in the linear range

• Quantitative assessment approaches:

  • Use digital image analysis for IHC/IF to obtain objective measurements

  • Employ fluorescence-based Western blot systems for more accurate quantification

  • Consider bead-based assays or ELISA for high-throughput quantification

  • Calculate coefficients of variation (CV) across technical replicates

• Multi-method validation:

  • Confirm key findings using at least two independent techniques

  • Correlate protein detection with mRNA levels (RT-qPCR, RNA-seq)

  • Consider mass spectrometry-based approaches for absolute quantification

  • Verify functional consequences of expression changes (e.g., effects on NRF2 levels)

• Statistical approaches to account for technical variation:

  • Run multiple technical replicates (at least triplicates)

  • Use appropriate statistical tests that account for experimental variation

  • Consider batch correction methods for large-scale studies

  • Calculate and report confidence intervals for all measurements

• Documentation of technical parameters:

  • Record detailed protocols including minor variations

  • Document antibody sources, catalog numbers, and lot numbers

  • Note any deviations from standard protocols

  • Use consistent data analysis pipelines

What controls are essential when using FAM117B antibodies for co-immunoprecipitation experiments?

When performing co-immunoprecipitation (Co-IP) experiments with FAM117B antibodies, several essential controls are required to ensure reliable and interpretable results:

• Input controls:

  • Include an aliquot of the pre-IP lysate (typically 5-10%) to verify protein expression

  • Use this to normalize IP efficiency across different samples

  • Confirm expression of both FAM117B and its potential interaction partners (e.g., KEAP1)

• Negative controls for antibody specificity:

  • IgG control: Perform parallel IP with isotype-matched non-specific IgG

  • Blocking peptide: Pre-incubate antibody with immunizing peptide to block specific binding

  • Genetic deletion: Use lysates from FAM117B knockdown cells

  • Irrelevant antibody: Use an antibody against an unrelated protein

• Reverse Co-IP validation:

  • Perform reciprocal IP using antibodies against the interaction partner (e.g., KEAP1)

  • Probe for FAM117B in the immunoprecipitate

  • This approach has been successfully used to validate FAM117B-KEAP1 interaction

• Controls for interaction specificity:

  • Mutant controls: Use cells expressing FAM117B with mutated interaction domains (e.g., ETGE motif mutants)

  • Domain mapping: Use truncated constructs to identify specific interaction regions

  • Competitive peptides: Add synthetic peptides containing the interaction motif

• Technical controls:

  • Bead-only control: Incubate lysate with beads in the absence of antibody

  • Crosslinking validation: If using crosslinkers, include non-crosslinked controls

  • Detergent sensitivity: Test different lysis conditions to confirm true interactions

  • RNase/DNase treatment: Eliminate nucleic acid-mediated associations if relevant

• Positive controls:

  • Include a well-established protein-protein interaction as procedural control

  • For FAM117B-KEAP1 interaction, consider using NRF2-KEAP1 as a positive control

• Expression level controls:

  • Compare native expression with overexpression systems

  • Be cautious about overexpression artifacts

  • Research has validated FAM117B-KEAP1 interaction at both endogenous levels and in overexpression systems

Implementation of these controls will help distinguish true FAM117B interactions from artifacts, providing reliable data on its role in the KEAP1/NRF2 pathway and other potential signaling networks.

How can the specificity of FAM117B antibodies be confirmed in the context of cancer tissue heterogeneity?

Confirming FAM117B antibody specificity in heterogeneous cancer tissues requires a multifaceted approach:

• Comprehensive validation using patient-matched materials:

  • Compare antibody staining in tumor tissue versus adjacent normal tissue

  • Analyze FAM117B expression at both protein (IHC/IF) and mRNA (in situ hybridization) levels

  • Perform laser capture microdissection followed by Western blot or mass spectrometry

  • Correlate antibody staining with RNAseq data from the same samples when possible

• Genetic model validation in tissue context:

  • Use tissue from xenograft models with FAM117B knockdown or overexpression

  • Compare antibody staining patterns in these models

  • Include xenografts with mutated FAM117B (particularly ETGE motif mutants)

  • Patient-derived xenografts provide a more realistic tissue context for validation

• Multi-antibody approach:

  • Use multiple antibodies targeting different epitopes of FAM117B

  • Compare staining patterns and intensity distributions

  • Consistent staining across antibodies increases confidence in specificity

  • Document epitope information for all antibodies used

• Multiplexed detection systems:

  • Perform multiplexed IF for FAM117B, KEAP1, and NRF2

  • Analyze co-localization patterns (FAM117B and KEAP1 should co-localize in the cytoplasm)

  • Correlate with functional markers (e.g., NRF2 nuclear localization)

  • Use spectral unmixing to minimize autofluorescence interference

• Peptide competition and absorption controls:

  • Pre-absorb antibody with recombinant FAM117B protein or immunizing peptide

  • Apply to serial sections of the same tumor

  • Complete signal abolishment indicates specificity

  • Partial reduction may indicate cross-reactivity with related proteins

• Heterogeneity-aware sampling approach:

  • Analyze multiple regions within the same tumor

  • Use tissue microarrays with multiple cores per tumor

  • Compare primary tumors with metastatic lesions

  • Document variations in FAM117B expression across different tumor regions

• Digital pathology quantification:

  • Use machine learning algorithms to classify cells and quantify staining

  • Develop scoring systems that account for intensity and distribution

  • Compare with manual scoring by multiple pathologists

  • Correlate with clinical outcomes as FAM117B and NRF2 co-overexpression predicts poor prognosis

By implementing these approaches, researchers can confidently assess FAM117B expression in heterogeneous cancer tissues while minimizing the risk of false-positive or false-negative results.

What novel approaches could improve the development of highly specific FAM117B antibodies?

Several innovative approaches could enhance the development of highly specific FAM117B antibodies:

• Structure-guided antibody design:

  • Determine the three-dimensional structure of FAM117B protein

  • Identify surface-exposed epitopes unique to FAM117B

  • Design antibodies specifically targeting these unique structural elements

  • Focus on regions distinct from the conserved ETGE motif to avoid cross-reactivity with other KEAP1-binding proteins

• Phage display with negative selection strategies:

  • Implement rigorous negative selection against related proteins

  • Include sequential panning against recombinant FAM117B protein

  • Incorporate counter-selection with lysates from FAM117B knockout cells

  • Select clones with high affinity and specificity ratios

• Single B-cell sequencing approaches:

  • Isolate B cells from immunized animals

  • Perform single-cell RNA sequencing to identify antibody sequences

  • Express and screen multiple antibody candidates simultaneously

  • Select candidates with optimal binding characteristics

• Conformation-specific antibody development:

  • Generate antibodies that specifically recognize FAM117B in its KEAP1-bound state

  • Develop antibodies that distinguish between active and inactive conformations

  • Create antibodies that selectively detect the ETGE motif when not engaged with KEAP1

• CRISPR-based validation pipeline:

  • Develop FAM117B knockout cell lines using CRISPR/Cas9

  • Use these lines for comprehensive antibody validation

  • Create CRISPR knock-in cell lines expressing epitope-tagged FAM117B

  • Establish domain-swapped variants for epitope mapping

• Machine learning-guided antibody optimization:

  • Apply computational approaches similar to DyAb to optimize antibody sequences

  • Train models using data from existing FAM117B antibodies

  • Optimize binding affinity and specificity simultaneously

  • Rank and prioritize candidate antibodies for experimental validation

• Bispecific antibody approaches:

  • Develop antibodies that simultaneously target FAM117B and KEAP1

  • Create reagents specific for the FAM117B-KEAP1 complex

  • Design antibodies that selectively recognize FAM117B in cancer versus normal cells

  • Incorporate therapeutic potential by targeting the functional ETGE motif

• Nanobody and alternative scaffold development:

  • Explore nanobodies (VHH domains) for improved access to conformational epitopes

  • Investigate aptamers as alternative binding reagents

  • Develop DARPins or affibodies with high specificity for FAM117B

  • These smaller formats may access epitopes unavailable to conventional antibodies

These approaches would address current limitations in FAM117B antibody specificity, particularly important given its role in the KEAP1/NRF2 pathway and implications for cancer progression .

How might emerging single-cell techniques enhance our understanding of FAM117B expression in tumor heterogeneity?

Emerging single-cell techniques offer powerful approaches to understand FAM117B expression in the context of tumor heterogeneity:

• Single-cell RNA sequencing (scRNA-seq):

  • Profile FAM117B mRNA expression at single-cell resolution across different tumor regions

  • Identify cell subpopulations with varying FAM117B expression levels

  • Correlate FAM117B expression with cell states and differentiation trajectories

  • Analyze co-expression patterns with NRF2, KEAP1, and other pathway components

  • Characterize transcriptional signatures associated with FAM117B-high versus FAM117B-low cells

• Single-cell proteomics approaches:

  • Apply mass cytometry (CyTOF) with FAM117B antibodies to quantify protein expression

  • Implement microfluidic-based single-cell Western blotting

  • Use single-cell proteomic technologies like SCoPE-MS (Single Cell ProtEomics by Mass Spectrometry)

  • Correlate FAM117B protein levels with activation states of signaling pathways

• Spatial transcriptomics and proteomics:

  • Map FAM117B expression in the spatial context of the tumor microenvironment

  • Use technologies like 10x Visium, Slide-seq, or GeoMx Digital Spatial Profiler

  • Correlate FAM117B expression with microenvironmental features (e.g., hypoxic regions, invasive front)

  • Analyze co-expression with NRF2 and KEAP1 in spatially defined niches

• Multimodal single-cell analysis:

  • Combine RNA and protein measurements at single-cell level (CITE-seq)

  • Integrate with chromatin accessibility (ATAC-seq) to understand FAM117B regulation

  • Analyze cell-cell communication networks influenced by FAM117B expression

  • Study how FAM117B-expressing cells interact with the tumor microenvironment

• Single-cell functional genomics:

  • Perform CRISPR screens at single-cell resolution to identify genes that interact with FAM117B

  • Use perturb-seq approaches to systematically manipulate FAM117B and measure consequences

  • Apply single-cell CRISPR imaging to monitor dynamic responses to FAM117B perturbation

  • Identify synthetic lethal interactions that could be therapeutically exploited

• Live-cell imaging of FAM117B dynamics:

  • Develop FAM117B reporter cell lines (e.g., CRISPR knock-in of fluorescent tags)

  • Track FAM117B localization and interaction with KEAP1 in real-time

  • Monitor dynamic responses to oxidative stress and chemotherapeutic agents

  • Quantify cell-to-cell variability in FAM117B-KEAP1-NRF2 dynamics

• Single-cell drug response profiling:

  • Correlate FAM117B expression with response to chemotherapeutic agents at single-cell level

  • Identify resistant cell populations with distinct FAM117B/NRF2 expression patterns

  • Test FAM117B-targeting strategies in heterogeneous cell populations

  • Develop personalized therapeutic approaches based on cellular composition

These single-cell approaches would provide unprecedented insights into how FAM117B heterogeneity contributes to tumor progression, chemoresistance, and poor patient outcomes , potentially leading to more precise therapeutic strategies.

What therapeutic potential does targeting the FAM117B-KEAP1 interaction have in cancer treatment?

Targeting the FAM117B-KEAP1 interaction represents a promising therapeutic strategy in cancer treatment, particularly in gastric cancer:

• Mechanistic rationale for therapeutic targeting:

  • FAM117B promotes cancer cell growth and chemoresistance through competing with NRF2 for KEAP1 binding

  • Disrupting this interaction could restore KEAP1-mediated NRF2 degradation

  • This would potentially re-sensitize cancer cells to chemotherapeutic agents

  • Studies have shown that FAM117B-induced growth and chemoresistance are NRF2-dependent

• Potential therapeutic modalities:

  • Small molecule inhibitors: Design compounds that specifically block the interaction between FAM117B's ETGE motif and KEAP1

  • Peptide-based therapeutics: Develop stapled peptides that mimic the KEAP1-binding region of NRF2 with higher affinity than FAM117B

  • Antibody-based approaches: Create antibodies that specifically target the ETGE motif of FAM117B

  • Proteolysis targeting chimeras (PROTACs): Design bifunctional molecules that bind FAM117B and recruit E3 ubiquitin ligases for degradation

• Target patient populations:

  • Gastric cancer patients with FAM117B and NRF2 co-overexpression, which is associated with poor prognosis

  • Patients with chemoresistant tumors showing high FAM117B expression

  • Cases with activated KEAP1/NRF2 signaling despite wild-type KEAP1 and NRF2

• Combination therapy strategies:

  • Combine FAM117B-KEAP1 interaction inhibitors with conventional chemotherapeutic agents

  • Explore synergies with other targeted therapies in gastric cancer

  • Consider sequential therapy to prevent resistance development

  • Test combinations with immunotherapies, as NRF2 activation may affect immune cell function

• Preclinical validation approaches:

  • Test in cell line panels with varying FAM117B and NRF2 expression levels

  • Evaluate in patient-derived xenograft models

  • Use xenograft models similar to those described in the literature

  • Assess effects on tumor growth, angiogenesis, and apoptosis

• Potential challenges and considerations:

  • Achieving specificity for FAM117B-KEAP1 interaction without affecting NRF2-KEAP1 interaction in normal cells

  • Developing methods to deliver therapeutic agents to tumor cells

  • Identifying predictive biomarkers for patient selection

  • Managing potential toxicities from altering redox homeostasis

• Translational research priorities:

  • Develop companion diagnostics to measure FAM117B-KEAP1 interaction

  • Establish pharmacodynamic markers of successful target engagement

  • Create patient-derived organoid models for drug screening

  • Initiate biomarker-driven clinical trials in stratified patient populations

Given that FAM117B promotes gastric cancer growth and chemoresistance by activating the KEAP1/NRF2 pathway , therapeutic strategies targeting this interaction could potentially improve outcomes for patients with currently limited treatment options.

How might advanced computational methods improve FAM117B antibody design and validation?

Advanced computational methods offer significant opportunities to enhance FAM117B antibody design and validation:

• Structure-based antibody design:

  • Predict the 3D structure of FAM117B using AlphaFold2 or similar AI models

  • Identify optimal epitopes based on surface accessibility, uniqueness, and stability

  • Simulate antibody-antigen interactions using molecular dynamics

  • Focus on regions that are functionally important (e.g., regions near but distinct from the ETGE motif)

  • Design antibodies that can distinguish between KEAP1-bound and unbound FAM117B states

• AI-driven antibody engineering:

  • Apply deep learning approaches similar to DyAb to optimize antibody sequences

  • Train models on existing antibody-antigen complex data

  • Predict binding affinity and specificity improvements for candidate antibodies

  • Design antibodies with optimal biophysical properties (stability, solubility, expression)

  • Generate sequence-diverse antibody candidates targeting the same epitope

• Epitope mapping and cross-reactivity prediction:

  • Identify potential cross-reactive proteins using structural similarity searches

  • Apply proteomic sequence analysis to identify unique regions of FAM117B

  • Predict epitope immunogenicity and antigenicity using machine learning algorithms

  • Estimate cross-reactivity risk with related proteins at the epitope level

  • Model the conformational flexibility of candidate epitopes

• Automated validation pipeline design:

  • Develop algorithms to design comprehensive validation experiments

  • Create statistical frameworks to quantitatively assess antibody specificity

  • Implement machine learning for automated image analysis of IHC/IF results

  • Design optimal control experiments using statistical power calculations

  • Generate synthetic negative controls using CRISPR-based approaches

• High-throughput screening simulation:

  • Model antibody expression and folding efficiency to prioritize candidates

  • Simulate antibody binding under different pH and ionic strength conditions

  • Predict stability under typical experimental conditions

  • Model binding kinetics and thermodynamics for antibody-antigen interactions

  • Estimate performance in different applications (Western blot, IHC, IP)

• Integrated multi-omics data analysis:

  • Correlate antibody-based protein quantification with RNA-seq data

  • Develop computational approaches to distinguish technical from biological variation

  • Integrate mass spectrometry data to validate antibody specificity

  • Create predictive models for antibody performance based on target protein features

  • Design visualization tools for complex antibody validation data

• Digital pathology and AI-based image analysis:

  • Develop deep learning algorithms for automated scoring of FAM117B IHC

  • Create models to detect staining artifacts versus true signal

  • Implement spatial analysis tools to assess heterogeneity in FAM117B expression

  • Design systems that can correlate FAM117B and NRF2 expression patterns

  • Develop quality control metrics for immunostaining reproducibility

These computational approaches would significantly enhance both the development of highly specific FAM117B antibodies and the validation processes needed to ensure their reliability in research and potential clinical applications.

What role might FAM117B play in cancer immunotherapy response and how can antibodies help investigate this?

FAM117B may play significant yet unexplored roles in cancer immunotherapy response, and antibodies will be crucial tools for investigating these potential mechanisms:

• Potential mechanisms linking FAM117B to immunotherapy response:

  • FAM117B activates the KEAP1/NRF2 pathway , which regulates oxidative stress and inflammation

  • NRF2 activation can modulate immune cell function and the tumor microenvironment

  • Altered ROS levels due to FAM117B expression may affect immune cell activation and function

  • FAM117B-mediated changes in tumor angiogenesis could impact immune cell infiltration

  • The KEAP1/NRF2 pathway influences expression of immune checkpoint molecules in some contexts

• Antibody-based investigation approaches:

  • Multiplex immunophenotyping:

    • Develop multiplexed IHC/IF panels including FAM117B, NRF2, and immune markers

    • Analyze spatial relationships between FAM117B-expressing tumor cells and immune infiltrates

    • Correlate FAM117B expression with PD-L1, PD-1, and other checkpoint molecules

    • Assess relationships between FAM117B expression and different immune cell populations

  • Flow cytometry applications:

    • Use FAM117B antibodies in multi-parameter flow cytometry

    • Analyze correlations between FAM117B expression and immune checkpoint expression

    • Sort FAM117B-high versus FAM117B-low tumor cells for functional studies

    • Investigate how FAM117B expression correlates with immune cell activation markers

• Co-culture experimental designs:

  • Co-culture FAM117B-manipulated tumor cells with:

    • T cells to assess cytotoxic activity and activation

    • Dendritic cells to study antigen presentation

    • Macrophages to evaluate polarization (M1 vs. M2)

  • Use FAM117B antibodies to monitor expression during immune interactions

  • Develop blocking antibodies targeting the ETGE motif to modulate FAM117B function in co-cultures

• In vivo immunotherapy models:

  • Generate FAM117B knockdown/overexpression in syngeneic mouse tumor models

  • Treat with immune checkpoint inhibitors and assess response differences

  • Analyze tumor immune microenvironment using FAM117B antibodies

  • Correlate FAM117B/NRF2 pathway activation with immunotherapy efficacy

• Biomarker development:

  • Develop IHC/IF protocols for FAM117B as a potential predictive biomarker

  • Create quantitative immunoassays for FAM117B in liquid biopsies

  • Analyze FAM117B expression in pre- and post-immunotherapy samples

  • Correlate FAM117B/NRF2 co-expression with immunotherapy response

• Mechanistic investigation tools:

  • Create function-blocking antibodies targeting the FAM117B ETGE motif

  • Develop antibodies that specifically detect the FAM117B-KEAP1 complex

  • Generate conformation-specific antibodies for active versus inactive FAM117B

  • Design dual-specificity antibodies targeting both FAM117B and immune checkpoint molecules

• Clinical correlation studies:

  • Perform retrospective analysis of FAM117B expression in immunotherapy trials

  • Correlate FAM117B/NRF2 expression with response and survival outcomes

  • Analyze potential synergies between FAM117B targeting and immunotherapy

  • Develop patient stratification strategies based on FAM117B expression patterns

Given FAM117B's established role in modulating the tumor microenvironment through NRF2-dependent mechanisms , investigating its impact on immunotherapy response represents an important frontier in cancer research.